Collaborative Research: CyberTraining: Implementation: Medium: Cyber Training on Materials Genome Innovation for Computational Software (CyberMAGICS)

合作研究：网络培训：实施：媒介：计算软件材料基因组创新网络培训 (Cyber​​MAGICS)

• 批准号: 2118099
• 负责人: Pratibha Dev
• 金额: $ 40万
• 依托单位: Howard University
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2021
• 资助国家: 美国
• 起止时间: 2021-09-01 至 2025-08-31
• 项目状态: 未结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2118099&HistoricalAwards=false
• 关键词: Collaborative; Research; CyberTraining; Implementation; Medium

The computing landscape is evolving rapidly. Exascale computers can perform unprecedented mathematical operations per second, while quantum computers have surpassed the computing power of the fastest supercomputers. Concomitantly, artificial intelligence (AI) is transforming every aspect of science and engineering. To address these rapid changes and challenges, this project will train a new generation of materials cyberworkforce, who will solve challenging materials genome problems through innovative use of advanced cyberinfrastructure (CI) at the exa-quantum/AI nexus. Further, the project will foster the adoption of exa-quantum/AI nexus technologies by a broad research community and beyond through a unique dual-degree PhD/MS program, undergraduate research to close the research-education gap, and broadening participation of women and underrepresented groups.This project will develop training modules for a new generation quantum materials simulator named AIQ-XMaS (AI and quantum-computing enabled exascale materials simulator), which integrates exa-scalable quantum, reactive and neural-network molecular dynamics simulations with unique AI and quantum-computing capabilities to study a wide range of materials and devices of high societal impact such as optoelectronics and pandemic preparedness. CyberMAGICS (cyber training on materials genome innovation for computational software) portal will be developed as a single-entry access point to all training modules that include step-by-step instructions in Jupyter notebooks and associated tutorial slides/videos, while providing online cloud service for those who do not have access to computing platform. The modules will be incorporated into the open-source AIQ-XMaS software suite as tutorial examples, and they will be piloted in classroom and workshop settings to directly train 1,200 CI users at the University of Southern California (USC) and Howard University, with a strong focus on underrepresented groups. Broader reach and training will be accomplished through the portal and nanoHUB. Students trained in the dual-degree program will earn a PhD in materials science or physics; they will also earn either an MS in computer science specialized in high-performance computing and simulations, MS in quantum information science, or MS in materials engineering with machine learning. Undergraduate students will be mentored and trained by academic scholars in multidisciplinary fields as well as by scientists at national labs and industry. The project will further broaden participation through USC’s Women in Science and Engineering (WiSE) program and undergraduate research by underrepresented groups jointly supervised by USC and Howard faculty.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

计算领域正在迅速发展。Exascale计算机每秒可以执行前所未有的数学运算，而量子计算机的计算能力已经超过了最快的超级计算机。与此同时，人工智能（AI）正在改变科学和工程的各个方面。为了应对这些快速变化和挑战，该项目将培训新一代材料网络工作人员，他们将通过在exa-quantum/AI关系中创新使用先进的网络基础设施（CI）来解决具有挑战性的材料基因组问题。此外，该项目将通过独特的双学位博士/硕士课程，促进广泛的研究社区及其他领域采用exa-quantum/AI nexus技术，本科研究以缩小研究教育差距，该项目将为新一代量子材料模拟器AIQ-XMaS开发培训模块，（AI和量子计算支持的exascale材料模拟器），它将exa可扩展的量子，反应和神经网络分子动力学模拟与独特的AI和量子计算能力相结合，以研究各种具有高度社会影响的材料和设备，如光电子和流行病准备。CyberMAGICS（计算软件材料基因组创新的网络培训）门户网站将被开发为所有培训模块的单一入口接入点，其中包括Cyberyter笔记本和相关教程幻灯片/视频中的分步说明，同时为那些无法访问计算平台的人提供在线云服务。这些模块将作为教程示例纳入开源AIQ-XMaS软件套件，并将在课堂和研讨会环境中进行试点，以直接培训南加州大学和霍华德大学的1，200名CI用户，重点关注代表性不足的群体。将通过门户网站和nanoHUB实现更广泛的接触和培训。在双学位课程中接受培训的学生将获得材料科学或物理学博士学位;他们还将获得专门从事高性能计算和模拟的计算机科学硕士学位，量子信息科学硕士学位或材料工程与机器学习硕士学位。本科生将由多学科领域的学术学者以及国家实验室和工业界的科学家指导和培训。该项目将通过南加州大学的妇女在科学和工程（WiSE）计划和本科生研究，由南加州大学和霍华德教师共同监督的代表性不足的群体进一步扩大参与。这个奖项反映了NSF的法定使命，并已被认为是值得通过使用基金会的智力价值和更广泛的影响审查标准进行评估的支持。

项目成果

CyberMAGICS: Cyber Training on Materials Genome Innovation for Computational Software for Future Engineers

• DOI: 10.18260/1-2-118.1112.1153-45660
• 期刊: 2023 PSW Proceedings
• 作者: K. Nomura;Pratibha Dev;A. Nakano;P. Vashishta;Tao Wei

Charge Transport through Superexchange in Phenothiazine–7,7,8,8-Tetracyanoquinodimethane (PTZ–TCNQ) Cocrystal Microribbon FETs Grown Using Evaporative Alignment

• DOI: 10.1021/acsaelm.2c01160
• 发表时间: 2022-11
• 期刊: ACS Applied Electronic Materials
• 影响因子: 4.7
• 作者: S. Melis;Samantha T. Hung;C. Bagade;Y. Chung;Eleni Hughes;Xinran Zhang;P. Barbara;P. Han;Tingting Li;Daniel McCusker;Robert Hartsmith;Jeffery A. Bertke;P. Dev;Iris Stone;Jaydeep Joshi;P. Vora;E. Van Keuren

Graphic contrastive learning analyses of discontinuous molecular dynamics simulations: Study of protein folding upon adsorption

• DOI: 10.1063/5.0157933
• 发表时间: 2023-06-19
• 期刊: APPLIED PHYSICS LETTERS
• 影响因子: 4
• 作者: Zheng，Size;Wei，Yong;Wei，Tao
• 通讯作者: Wei，Tao